Himalayas Jobs Scraper

Every remote job on Himalayas, in a clean flat schema, with each posting scored for how likely it is to still be open.

Himalayas is one of the better remote job boards — it's the only major one that publishes an explicit expiry date and numeric timezone restrictions on every listing. This Actor uses both, and hands you a dataset you can filter and query rather than a dump you have to clean.

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What each row contains

Identity	stable id across runs, posting URL, direct applyUrl
The role	title, company, plain-text description, tags, employment type, seniority
Where	normalised regions (worldwide / usa / canada / latam / uk / europe / apac / africa / middle_east) plus timezone restrictions as UTC+2-style tokens
Pay	min, max, currency and period as numbers — annualised on request so hourly and monthly rates compare correctly
When	posted date, expiry date, age in days
Trust	freshness 0–1, ghostRisk low/medium/high, and ghostReason explaining the verdict in plain words

The trust fields

Job boards are full of postings that are still published but no longer open. Because Himalayas publishes a real expiry date, the risk scoring here is unusually well-grounded — an expired posting is detected outright rather than inferred from age.

{
  "title": "Senior Backend Engineer",
  "company": "Acme",
  "regions": ["worldwide"],
  "timezoneRestrictions": ["UTC-5", "UTC-4", "UTC-3"],
  "salaryMin": 120000, "salaryMax": 160000,
  "salaryCurrency": "USD", "salaryPeriod": "year",
  "freshness": 0.71,
  "ghostRisk": "low",
  "ghostReason": ["recent, and nothing contradicts it"]
}

Freshness decays on a 21-day half-life. A posting with no date scores 0.5, not 1.0 — absence of evidence is not evidence of freshness.

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Example input

{
  "query": ["golang", "backend", "platform"],
  "regions": ["usa", "europe"],
  "seniority": ["senior", "lead"],
  "maxGhostRisk": "low",
  "salaryOnly": true,
  "maxItems": 200
}

Everything is optional — run it empty and you get the whole board, best-first.

Worth knowing:

• Search terms are OR-ed. ["go", "rust"] returns jobs mentioning either.
• Worldwide jobs match every region filter, because a job open to everyone is open to you.
• minSalary is annualised first, so hourly and monthly rates compare correctly.
• maxItems is your cost ceiling — you're billed per job returned.
• maxPagesPerSource controls depth. Himalayas serves 20 jobs per page and ignores any limit parameter, so 10 pages is roughly 200 jobs and 35 is roughly 700.

Output

One dataset item per job, ordered best-first: lowest ghost-job risk, then freshest. Export as JSON, CSV or Excel, or pull it from the API like any Apify dataset.

Common uses

• Filtering out expired and stale job postings. ghostRisk, ghostReason and freshness say which listings are probably no longer open. Himalayas publishes a real expiry date, so here that judgement is grounded rather than inferred.
• Salary benchmarking and compensation data. salaryMin, salaryMax, salaryCurrency and salaryPeriod are numbers, not strings, and minSalary annualises before comparing — so hourly, monthly and yearly postings line up.
• Timezone-restricted remote hiring. timezoneRestrictions and normalised regions let you keep only the jobs someone in your timezone can actually take, instead of "remote" that means "remote if you live in Berlin".
• Remote job market and hiring data. Run it on a schedule and track how remote hiring, salary ranges, seniority mix and regions move over time.
• Building a job board, job feed or job alerts. id is stable across runs, so diffing today's dataset against yesterday's gives you genuinely new jobs rather than a board reshuffle.
• Recruitment and talent research. Company, title, tags, seniority, employment type and normalised regions on every row.

Export as JSON, CSV or Excel, or read the dataset straight from the Apify API.

How it fetches

Himalayas publishes a public, documented, unauthenticated JSON API and this Actor reads it — paced, budgeted, with an honest user agent. No HTML scraping, no bot-check evasion, no personal data. Job adverts only.

How to scrape Himalayas jobs with this Actor

1. Open the Actor and press Start. With no input it returns every remote job Himalayas currently lists, best-first.
2. Narrow it when you need to: search terms, hiring regions, seniority, a minimum salary, a maximum ghost-job risk, and maxItems as a hard cost ceiling. maxPagesPerSource sets the depth: 10 pages is roughly 200 jobs, 35 is roughly 700.
3. Export the dataset as JSON, CSV or Excel, read it through the Apify API, or schedule the run and attach a webhook or an integration (Google Sheets, Make, Zapier, Slack) so new Himalayas jobs arrive on their own.

How much does it cost to scrape Himalayas?

You pay per job returned, on Apify's pay-per-event model: $0.006 per job on the Free and Bronze plans, $0.003 on Silver, $0.002 on Gold and above, with no platform usage charged on top. A run that returns nothing costs nothing. The default 10 pages is roughly 200 jobs, about $1.20 on the Free tier. Set maxItems to cap a run, and Apify's free plan includes a monthly usage credit, so a first run costs nothing out of pocket.

Related Actors from the same pipeline

• Remote Jobs Aggregator — six boards in one call, deduplicated, with salary parsing and ghost-job scoring
• RemoteOK Jobs Scraper — genuinely remote developer jobs, the on-site leakage filtered out
• Remotive Jobs Scraper — a small, hand-curated board of remote tech jobs
• Arbeitnow Jobs Scraper — Germany and Europe, remote and on-site, the largest single feed
• We Work Remotely Scraper — company split from title, real expiry dates
• Jobicy Jobs Scraper — the cleanest structured salary data for benchmarking
• Dice Jobs Scraper — US tech jobs with salary parsed to the cent

All eight share one schema, one ghost-job model and one set of filters, so a query written for this board runs unchanged against any of the others.

FAQ

Does Himalayas have an official API, and is it allowed to scrape it? Himalayas publishes a public, documented, unauthenticated JSON API and this Actor reads it — paced, budgeted, with an honest user agent. No HTML scraping, no bot-check evasion, no personal data. Job adverts only.

How often does Himalayas post new jobs, and how often should I run this? New listings appear every day. A daily schedule keeps the dataset current, and because id is stable across runs, diffing today's dataset against yesterday's yields only the genuinely new Himalayas jobs, not a reshuffle.

How do I get only fresh, still-open Himalayas jobs? Set maxGhostRisk to low. Himalayas publishes a real expiry date on every listing, so an expired posting is detected outright here rather than inferred from age; maxAgeDays tightens it further, and every row carries ghostReason if you would rather apply your own rule.

What is a ghost job? A posting that is still published but no longer open: a filled role left up for pipeline, an evergreen "talent pool" advert, or a listing on a board that never expires anything. The ghostRisk band and freshness score flag them from what the board itself publishes — age, expiry dates, missing application links, evergreen phrasing — never from a model's guess.

Does it include salaries? Where Himalayas publishes pay, yes: salaryMin, salaryMax, salaryCurrency and salaryPeriod are parsed into numbers and annualised on request. Set salaryOnly to keep only rows with a published salary.

Can I filter Himalayas jobs by timezone? Yes. Himalayas is the one major board that publishes numeric timezone restrictions, and they come through as UTC+2-style tokens in timezoneRestrictions, beside the normalised regions.

Do I need proxies, a login or an API key? No. Himalayas is read the way it asks to be read, and Apify runs the Actor for you; nothing to install and no credentials to manage.

Can I export Himalayas jobs to CSV, Excel or Google Sheets? Yes. Every run's dataset downloads as JSON, CSV or Excel from the Apify Console or API, and the Google Sheets integration writes rows straight into a sheet.

Want more than one board?

Remote Jobs Aggregator runs this same pipeline across six boards at once — Himalayas, Remote OK, Remotive, Arbeitnow, We Work Remotely and Jobicy — folding duplicates and marking which boards carry each job.

Useful thing measured while building it: those six boards barely overlap. Only 1 of 1,513 company+title pairs appeared on more than one. So the aggregator isn't about removing duplication — there almost isn't any — it's about getting six boards' worth of distinct jobs in one query.